Are you into volatility watching? Are you looking for the short end of the curve … shorter than one day? You found it! Peek at yarx streams and perhaps xray too. An approximate description is the code that generates them but TBH that isn’t quite the code that runs.
Oh yeah. There are prizes on offer for aggregate performance as you may have noticed on the sub-leaderboards.
Stock and protfolio streams
These are intended to provide “xray vision” into the joint behaviour of stocks. The portfolio weights are provided as JSON.
| Type | Example stream | Lookup | Reverse lookup |
|---|---|---|---|
| Stocks | stream=quick_yarx_googl | xraytickers.json | xraytickersreverse.json |
| Portfolios | stream=quick_xray_3 | portfolios.json | |
| Stocks | stream=middling_yarx_googl | xraytickers.json | xraytickersreverse.json |
| Portfolios | stream=middling_xray_3 | portfolios.json | |
| Stocks | stream=slow_yarx_googl | xraytickers.json | xraytickersreverse.json |
| Portfolios | stream=slow_xray_3 | portfolios.json |
Only 1 hour ahead predictions are considered relevant for prizes.
Volatility streams
There are derived feature streams
| Type | Example stream | Meaning |
|---|---|---|
| Vol | stream=yarx_vlty_0_aapl | Scaled log of middling_yarx_appl predictions interquartile range |
| Vol slope | stream=yarx_vlty_1_aapl | Difference between scaled log quick and log slow inter-quartile ranges |
| Vol convexity | stream=yarx_vlty_2_aapl | Similar, but the convexity |
Exogenous data streams
Some exogenous features are being added that tick infrequently. They may be useful in your models, however.
| Type | Example stream | Meaning |
|---|---|---|
| Vol | stream=yarx_exog_0_aapl | Vol feature |
(ignore any exog_yarx streams they are deprecated)
Universe
Roughly, the top 100 stocks.
from microprediction.live.xraytickers import get_xray_tickers
from microprediction.live.xrayportfolios import get_xray_portfolios
symbols = get_xray_tickers()
weights = get_xray_portfolios()
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